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ICML
2003
IEEE
16 years 5 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
169
Voted
IAT
2005
IEEE
15 years 10 months ago
Self-Organizing Cognitive Agents and Reinforcement Learning in Multi-Agent Environment
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
Ah-Hwee Tan, Dan Xiao
ML
2002
ACM
168views Machine Learning» more  ML 2002»
15 years 4 months ago
On Average Versus Discounted Reward Temporal-Difference Learning
We provide an analytical comparison between discounted and average reward temporal-difference (TD) learning with linearly parameterized approximations. We first consider the asympt...
John N. Tsitsiklis, Benjamin Van Roy
CCIA
2005
Springer
15 years 10 months ago
Direct Policy Search Reinforcement Learning for Robot Control
— This paper proposes a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, whe...
Andres El-Fakdi, Marc Carreras, Narcís Palo...
ICALP
2001
Springer
15 years 9 months ago
Separating Quantum and Classical Learning
We consider a model of learning Boolean functions from quantum membership queries. This model was studied in [26], where it was shown that any class of Boolean functions which is i...
Rocco A. Servedio